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Related Concept Videos

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

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Related Experiment Video

Updated: May 19, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

Assessing drug target association using semantic linked data.

Bin Chen1, Ying Ding, David J Wild

  • 1School of Informatics and Computing, Indiana University, Bloomington, IN, USA.

Plos Computational Biology
|August 4, 2012
PubMed
Summary
This summary is machine-generated.

This study integrates diverse chemical and biological data into a large network to predict drug targets. The developed model accurately identifies known drug-target relationships and suggests new drug pairings for diseases.

Related Experiment Videos

Last Updated: May 19, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

Area of Science:

  • Bioinformatics
  • Computational Chemistry
  • Drug Discovery

Background:

  • Increasing public data in chemistry and biology offers opportunities for large-scale data mining in drug discovery.
  • Integrating heterogeneous datasets and applying data mining algorithms can elucidate complex drug mechanisms of action.

Purpose of the Study:

  • To integrate and annotate public data for building a semantic linked network.
  • To develop a statistical model for assessing drug-target associations.
  • To provide a novel alternative to existing drug target prediction algorithms.

Main Methods:

  • Integrated and annotated data from public datasets (drugs, compounds, targets, diseases, pathways).
  • Built a semantic linked network with over 290,000 nodes and 720,000 edges.
  • Developed a statistical model to assess drug-target pair associations based on linked object relations.
  • Calculated association scores and similarity using a matrix for 157 drugs against 1683 human targets.

Main Results:

  • Successfully created a large semantic linked network.
  • The statistical model accurately identified known direct drug-target pairs with high precision.
  • Indirect drug-target pairs were also identified, though with lower confidence.
  • A similarity network revealed that drugs from the same disease area cluster together, suggesting potential new drug pairings.

Conclusions:

  • The developed semantic network and association model offer a validated, novel approach to drug target prediction.
  • The findings highlight the potential for identifying new therapeutic strategies by analyzing drug-target relationships within disease contexts.
  • The freely available web service facilitates further research in drug discovery and target identification.